Polish Academic MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the return format ('Returns JSON: title, authors, epochs, genres, download links...') and hints at data structure ('children volumes, optional fragment preview'), which is valuable. However, it doesn't mention error handling, rate limits, authentication needs, or whether this is a read-only operation, leaving some behavioral aspects unclear for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose in the first clause, followed by return details and usage guidance. Every sentence adds essential information—no wasted words. It efficiently covers purpose, output, and sibling tool relationships in three concise sentences.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (1 parameter, no nested objects) and lack of output schema, the description does a good job of explaining what the tool does, what it returns, and how to use it with siblings. However, without annotations or output schema, it could benefit from more behavioral details (e.g., error cases, read-only nature) to be fully complete, though it's sufficient for basic use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with the parameter 'slug' well-documented in the schema. The description adds minimal value beyond the schema by providing examples ('e.g. lalka, pan-tadeusz') and context about slug sources ('from /katalog/lektura/{slug}/ or API href'), but doesn't explain semantics like format constraints or validation rules. With high schema coverage, a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Fetch one book') and resource ('from Wolne Lektury'), distinguishing it from siblings like wolnelektury_filter_books (which filters) and wolnelektury_list_taxonomy (which lists categories). It specifies the retrieval mechanism ('by URL slug') and the scope ('one book'), making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly provides when to use this tool ('Fetch one book... by URL slug') and offers clear alternatives for discovering slugs ('via wolnelektury_list_taxonomy and wolnelektury_filter_books or from wolnelektury.pl catalog URLs'). This gives the agent direct guidance on when to use this tool versus its siblings for different tasks.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.